scholarly journals Integrating Casein Complex SNPs Additive, Dominance and Epistatic Effects on Genetic Parameters and Breeding Values Estimation for Murciano-Granadina Goat Milk Yield and Components

Genes ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 309 ◽  
Author(s):  
María Gabriela Pizarro Inostroza ◽  
Vincenzo Landi ◽  
Francisco Javier Navas González ◽  
Jose Manuel León Jurado ◽  
Juan Vicente Delgado Bermejo ◽  
...  
Keyword(s):  
Milk Yield ◽  
Genetic Parameters ◽  
Genetic Regulation ◽  
Principal Component ◽  
Nonparametric Tests ◽  
Genetic Effects ◽  
Prediction Errors ◽  
Production Traits ◽  
Breeding Values ◽  
Epistatic Effects

Assessing dominance and additive effects of casein complex single-nucleotide polymorphisms (SNPs) (αS1, αS2, β, and κ casein), and their epistatic relationships may maximize our knowledge on the genetic regulation of profitable traits. Contextually, new genomic selection perspectives may translate this higher efficiency into higher accuracies for milk yield and components’ genetic parameters and breeding values. A total of 2594 lactation records were collected from 159 Murciano-Granadina goats (2005–2018), genotyped for 48 casein loci-located SNPs. Bonferroni-corrected nonparametric tests, categorical principal component analysis (CATPCA), and nonlinear canonical correlations were performed to quantify additive, dominance, and interSNP epistatic effects and evaluate the outcomes of their inclusion in quantitative and qualitative milk production traits’ genetic models (yield, protein, fat, solids, and lactose contents and somatic cells count). Milk yield, lactose, and somatic cell count heritabilities increased considerably when the model including genetic effects was considered (0.46, 0.30, 0.43, respectively). Components standard prediction errors decreased, and accuracies and reliabilities increased when genetic effects were considered. Conclusively, including genetic effects and relationships among these heritable biomarkers may improve model efficiency, genetic parameters, and breeding values for milk yield and composition, optimizing selection practices profitability for components whose technological application may be especially relevant for the cheese-making dairy sector.

Reduced-rank estimation of genetic parameters for egg production traits and cluster analyses with predicted breeding values

2018 ◽  
Vol 68 (2) ◽  
pp. 81-86
Author(s):  
Luara Afonso de Freitas ◽  
Rodrigo Pelicioni Savegnago ◽  
Natalia Vinhal Grupioni ◽  
Salvador Boccaletti Ramos ◽  
Nedenia Bonvino Stafuzza ◽  
...  
Keyword(s):  
Egg Production ◽  
Genetic Parameters ◽  
Production Traits ◽  
Breeding Values ◽  
Cluster Analyses ◽  
Rank Estimation ◽  
Reduced Rank ◽  
Estimation Of Genetic Parameters

scholarly journals Estimates of genetic parameters, and cluster and principal components analyses of breeding values related to egg production traits in a White Leghorn population

2011 ◽  
Vol 90 (10) ◽  
pp. 2174-2188 ◽  
Author(s):  
R.P. Savegnago ◽  
S.L. Caetano ◽  
S.B. Ramos ◽  
G.B. Nascimento ◽  
G.S. Schmidt ◽  
...  
Keyword(s):  
Principal Components ◽  
Egg Production ◽  
Genetic Parameters ◽  
Production Traits ◽  
White Leghorn ◽  
Breeding Values

scholarly journals Ten Genetic Loci Identified for Milk Yield, Fat, and Protein in Holstein Cattle

2020 ◽  
Author(s):  
Liyuan Liu ◽  
Jinghang Zhou ◽  
Chunpeng James Chen ◽  
Juan Zhang ◽  
Wan Wen ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Milk Production ◽  
Milk Yield ◽  
Genetic Variants ◽  
Holstein Cattle ◽  
Genome Wide Association Studies ◽  
Production Traits ◽  
Milk Production Traits ◽  
Breeding Values ◽  
Genome Wide

AbstractHigh-yield and high-quality of milk are the primary goals of dairy production. Understanding the genetic architecture underlying these milk production traits is beneficial so that genetic variants can be targeted toward the genetic improvement. In this study, we measured five milk production traits in Holstein cattle population from China. These traits included milk yield, protein yield, fat yields; fat percentage and protein percentages. We used the estimated breeding values as dependent variables to conduct the genome-wide association studies (GWAS). Breeding values were estimated through pedigree relationships by using a mixed linear model for individuals with and without phenotypic data. Genotyping was carried out on the individuals with phenotypes by using the Illumina BovineSNP150 BeadChip. The association analyses were conducted by using the Fixed and random model Circulating Probability Unification (FarmCPU) method. A total of ten SNPs was detected above the genome-wide significant threshold, including six located in previously reported QTL regions. We found eight candidate genes within distances of 120 kb upstream or downstream to the associated SNPs. The most significant SNP is on DGAT1 gene affecting milk fat and protein percentage. These genetic variants and candidate genes would be valuable resources to enhance dairy cattle breeding.

scholarly journals Random regression models to estimate genetic parameters for test-day milk yield and composition in Iranian buffaloes

2013 ◽  
Vol 56 (1) ◽  
pp. 276-284 ◽  
Author(s):  
M. Madad ◽  
N. Ghavi Hossein-Zadeh ◽  
A. A. Shadparvar ◽  
D. Kianzad
Keyword(s):  
Milk Yield ◽  
Milk Fat ◽  
Milk Protein ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Random Regression ◽  
Production Traits ◽  
Environmental Correlations ◽  
Protein Percentage ◽  
Heritability Estimates

Abstract. The objective of this study was to estimate genetic parameters for milk yield and milk percentages of fat and protein in Iranian buffaloes. A total of 9,278 test-day production records obtained from 1,501 first lactation buffaloes on 414 herds in Iran between 1993 and 2009 were used for the analysis. Genetic parameters for productive traits were estimated using random regression test-day models. Regression curves were modeled using Legendre polynomials (LPs). Heritability estimates were low to moderate for milk production traits and ranged from 0.09 to 0.33 for milk yield, 0.01 to 0.27 for milk protein percentage and 0.03 to 0.24 for milk fat percentage, respectively. Genetic correlations ranged from −0.24 to 1 for milk yield between different days in milk over the lactation. Genetic correlations of milk yield at different days in milk were often higher than permanent environmental correlations. Genetic correlations for milk protein percentage ranged from −0.89 to 1 between different days in milk. Also, genetic correlations for milk percentage of fat ranged from −0.60 to 1 between different days in milk. The highest estimates of genetic and permanent environmental correlations for milk traits were observed at adjacent test-days. Ignoring heritability estimates for milk yield and milk protein percentage in the first and final days of lactation, these estimates were higher in the 120 days of lactation. Test-day milk yield heritability estimates were moderate in the course of the lactation, suggesting that this trait could be applied as selection criteria in Iranian milking buffaloes.

scholarly journals Estimates of genetic parameters and cluster analyses for carcass and meat quality traits in birds

2017 ◽  
Vol 52 (3) ◽  
pp. 205-213 ◽  
Author(s):  
Adriane Molardi Bainy ◽  
Rodrigo Pelicioni Savegnago ◽  
Luara Afonso de Freitas ◽  
Beatriz do Nascimento Nunes ◽  
Jaqueline Oliveira Rosa ◽  
...  
Keyword(s):  
Meat Quality ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Meat Production ◽  
Quality Traits ◽  
Production Traits ◽  
Multiple Trait ◽  
Breeding Values ◽  
Cluster Analyses ◽  
Meat Quality Traits

Abstract: The objective of this work was to estimate genetic parameters for bird carcass and meat quality traits, as well as to explore the genetic patterns of the breeding values of this population using cluster analyses. Data from 1,846 birds were used to estimate the genetic parameters of production and quality traits using the multiple-trait animal model, and cluster analyses were performed. The heritability estimates ranged from 0.08± 0.03 for meat pH measured 24 hours after slaughter to 0.85± 0.09 for body weight. The genetic correlations between production traits were high and positive. The genetic correlations between meat quality traits were low and were not informative due to the high standard errors (same magnitudes as those of the genetic correlations). The genetic correlations between meat production and quality traits were negative, except between production traits and meat lightness intensity. Based on breeding values (EBVs), the evaluated population can be divided into four groups through cluster analyses, and one group is suitable for selection because the birds presented EBVs above and around the average of the population, respectively, for production and quality traits. Therefore, it is possible to obtain genetic gains for production-related traits without decreasing meat quality.

scholarly journals Genetic Effects of LPIN1 Polymorphisms on Milk Production Traits in Dairy Cattle

Genes ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 265 ◽  
Author(s):  
Bo Han ◽  
Yuwei Yuan ◽  
Ruobing Liang ◽  
Yanhua Li ◽  
Lin Liu ◽  
...  
Keyword(s):  
Milk Production ◽  
Milk Yield ◽  
Genetic Effects ◽  
Production Traits ◽  
Milk Production Traits ◽  
Association Analyses ◽  
Protein Percentage ◽  
Haplotype Blocks ◽  
Flanking Region ◽  
Fat Yield

Our initial RNA sequencing work identified that lipin 1 (LPIN1) was differentially expressed during dry period, early lactation, and peak of lactation in dairy cows, and it was enriched into the fat metabolic Gene Ontology (GO) terms and pathways, thus we considered LPIN1 as the candidate gene for milk production traits. In this study, we detected the polymorphisms of LPIN1 and verified their genetic effects on milk yield and composition in a Chinese Holstein cow population. We found seven SNPs by re-sequencing the entire coding region and partial flanking region of LPIN1, including one in 5′ flanking region, four in exons, and two in 3′ flanking region. Of these, four SNPs, c.637T > C, c.708A > G, c.1521C > T, and c.1555A > C, in the exons were predicted to result in the amino acid replacements. With the Haploview 4.2, we found that seven SNPs in LPIN1 formed two haplotype blocks (D′ = 0.98–1.00). Single-SNP association analyses showed that SNPs were significantly associated with milk yield, fat yield, fat percentage, or protein yield in the first or second lactation (p = < 0.0001–0.0457), and only g.86049389C > T was strongly associated with protein percentage in both lactations (p = 0.0144 and 0.0237). The haplotype-based association analyses showed that the two haplotype blocks were significantly associated with milk yield, fat yield, protein yield, or protein percentage (p = < 0.0001–0.0383). By quantitative real-time PCR (qRT-PCR), we found that LPIN1 had relatively high expression in mammary gland and liver tissues. Furthermore, we predicted three SNPs, c.637T > C, c.708A > G, and c.1521C > T, using SOPMA software, changing the LPIN1 protein structure that might be potential functional mutations. In summary, we demonstrated the significant genetic effects of LPIN1 on milk production traits, and the identified SNPs could serve as genetic markers for dairy breeding.

Genetic relationships between internal parasite resistance and production traits in Merino sheep

2017 ◽  
Vol 57 (2) ◽  
pp. 209 ◽  
Author(s):  
D. J. Brown ◽  
N. M. Fogarty
Keyword(s):  
Genetic Parameters ◽  
Genetic Correlations ◽  
Production Traits ◽  
Parasite Resistance ◽  
Breeding Programs ◽  
Sheep Breeding ◽  
Breeding Values ◽  
Merino Sheep ◽  
Internal Parasite ◽  
Australian Sheep

Breeding Merino sheep that are resistant to internal parasites alleviates the high costs associated with treatment of worm infestation and loss of production, as well as mitigating the development of anthelmintic resistance among the major worm species. Faecal worm egg count ((cube root transformation), wec) can be used in sheep as a measure of internal parasite resistance. Accurate estimates of genetic parameters for wec are required for calculation of Australian Sheep Breeding Values and inclusion of worm resistance in sheep breeding programs. This study provides updated estimates of heritability for wec and its genetic correlations with production traits. Data were analysed from a wide range of Australian and New Zealand Merino sheep in the MERINOSELECT database, which included 141 flocks with 801 flock years and up to 217 137 animals with wec recorded in at least one of four ages (W = weaning, P = post weaning, Y = yearling, H = hogget). The heritability estimates ranged from 0.16 ± 0.01 for Ywec to 0.29 ± 0.01 for Wwec, with generally high genetic correlations between the ages. Bivariate analyses estimated genetic correlations between wec at the various ages and growth, carcass quality, reproduction and wool production traits at various ages. These genetic correlations were generally small or close to zero, albeit with some significantly different from zero. The moderate heritability for wec (0.2–0.3) and its high phenotypic variation (coefficient of variation >30%) shows that relatively rapid selection response for worm resistance could be achieved. Inclusion of wec in sheep breeding programs to increase worm resistance would be expected to have little if any impact on other important production traits. These genetic parameters have been incorporated into MERINOSELECT by Sheep Genetics to provide Australian Sheep Breeding Values for wec and appropriate indices for wool and meat production. There is evidence that genotype × environment interactions may be important in some environments by reducing the accuracy of Australian Sheep Breeding Values for wec. Hence it may be prudent for breeders to implement strategies that manage the risk of any impact of genotype × environment on their breeding program.

scholarly journals Estimation of genetic parameters and prediction of breeding values for some economic traits of Black Bengal Goat under farming condition

2020 ◽  
Vol 20 (1-2) ◽  
pp. 8-17
Author(s):  
MA Jalil ◽  
S Akther ◽  
MP Choudhury ◽  
MA Habib
Keyword(s):  
Birth Weight ◽  
Litter Size ◽  
Milk Yield ◽  
Genetic Parameters ◽  
Breeding Values ◽  
Lactation Length ◽  
Total Milk ◽  
Daily Milk Yield ◽  
Black Bengal Goat ◽  
Daily Milk

The study was undertaken to evaluate the genetic progress of Black Bengal Goat (BBG) by estimating genetic parameters viz. heritability and breeding values for economically important productive and reproductive traits (birth weight, weight at 3, 6, 9 & 12 months, daily milk yield, lactation length, total milk yield and litter size of BBG goat population). Variance and co-variance components were analyzed applying Residual Maximum Likelihood (REML) approach by VCE 4.2.5 computer package. The heritability (h2) of birth weight was estimated as 0.2, which was low. The heritability estimates for 3-month weight (0.40), 6-month weight (0.50), 9-month weight (0.37) and 12-month weight (0.36) were found medium. Estimated h2 of daily milk yield, total milk yield and lactation length in this study were from 0.55 to 0.82.  h2 of litter size was 0.09. The maximum estimated breeding value (EBV) was found for 6 month body weight (12.94 kg), however, for daily milk yield, the value was 1.513 kg. The results found in this study revealed that genetic improvement of BBG for most of the traits is possible by selection and breeding. Bangladesh J. of Livestock Res. 20(1-2): 8-17, Jan-Dec 2013

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